Human-Centered learning analytics (HCLA) is an approach that emphasizes the human factors in learning analytics and truly meets user needs. User involvement in all stages of the design, analysis, and evaluation of learning analytics is the key to increase value and drive forward the acceptance and adoption of learning analytics. Visual analytics is a multidisciplinary data science research field that follows a human-centered approach and thus has the potential to foster the acceptance of learning analytics. Although various domains have already made use of visual analytics, it has not been considered much with respect to learning analytics. This paper explores the benefits of incorporating visual analytics concepts into the learning analytics process by (a) proposing the Learning Analytics and Visual Analytics (LAVA) model as enhancement of the learning analytics process with human in the loop, (b) applying the LAVA model in the Open Learning Analytics Platform (OpenLAP) to support humancentered indicator design, and (c) evaluating how blending learning analytics and visual analytics can enhance the acceptance and adoption of learning analytics, based on the technology acceptance model (TAM).
翻译:人本学习分析(HCLA)是一种强调学习分析中的人因素并真正满足用户需求的方法。在设计、分析和评估学习分析的所有阶段中,用户的参与是增加价值和推动学习分析得到接受和采纳的关键。视觉分析是一种跨学科的数据科学研究领域,遵循人本主义的方法,因此有潜力促进学习分析的接受。虽然众多领域已经利用视觉分析,但在学习分析方面尚未被充分考虑。本文探讨了将视觉分析概念纳入学习分析过程中的好处,通过(a)提出以人本作为支持点的LAVA模型,加强学习分析过程,(b)将LAVA模型应用于开放式学习分析平台(OpenLAP)以支持人本主义指标设计,(c)评估将学习分析和视觉分析混合使用如何增强学习分析的接受和采纳,基于技术接受模型(TAM)。